@article{MTMT:31868340,
	title = {Better understanding mathematics by algorithmic thinking and computer programming},
	url = {https://m2.mtmt.hu/api/publication/31868340},
	author = {Fried, Katalin and Fekete, István and Princz, Péter},
	doi = {10.5485/TMCS.2020.0486},
	journal-iso = {TEACH MATH COMP SCI},
	journal = {TEACHING MATHEMATICS AND COMPUTER SCIENCE},
	volume = {18},
	unique-id = {31868340},
	issn = {1589-7389},
	year = {2020},
	eissn = {2676-8364},
	pages = {295-305},
	orcid-numbers = {Fried, Katalin/0000-0002-4730-7582; Fekete, István/0000-0002-4089-4550}
}

@article{MTMT:31272377,
	title = {Programming Theorems and Their Applications},
	url = {https://m2.mtmt.hu/api/publication/31272377},
	author = {Fekete, István and Gregorics, Tibor and Kovácsné Pusztai, Kinga Emese and Veszprémi, Anna},
	doi = {10.5485/TMCS.2019.0466},
	journal-iso = {TEACH MATH COMP SCI},
	journal = {TEACHING MATHEMATICS AND COMPUTER SCIENCE},
	volume = {17},
	unique-id = {31272377},
	issn = {1589-7389},
	year = {2020},
	eissn = {2676-8364},
	pages = {213-241},
	orcid-numbers = {Fekete, István/0000-0002-4089-4550; Gregorics, Tibor/0000-0002-9503-9623; Kovácsné Pusztai, Kinga Emese/0000-0002-2300-2231}
}

@article{MTMT:32718759,
	title = {Antal Iványi (1942–2017)},
	url = {https://m2.mtmt.hu/api/publication/32718759},
	author = {Kása, Zoltán and Fekete, István},
	journal-iso = {ACTA UNIV SAP INFORM},
	journal = {ACTA UNIVERSITATIS SAPIENTIAE INFORMATICA},
	volume = {9},
	unique-id = {32718759},
	issn = {1844-6086},
	year = {2017},
	eissn = {2066-7760},
	pages = {5-16},
	orcid-numbers = {Fekete, István/0000-0002-4089-4550}
}

@book{MTMT:3191829,
	title = {Algoritmusok és adatszerkezetek},
	url = {https://m2.mtmt.hu/api/publication/3191829},
	isbn = {9789632484565},
	author = {Fekete, István and Hunyadvári, László},
	publisher = {Digitális Tankönyvtár},
	unique-id = {3191829},
	year = {2015},
	orcid-numbers = {Fekete, István/0000-0002-4089-4550}
}

@article{MTMT:2921814,
	title = {A Case Study of Advancing Remote Sensing Image Analysis},
	url = {https://m2.mtmt.hu/api/publication/2921814},
	author = {Giachetta, Roberto and Fekete, István},
	doi = {10.14232/actacyb.22.1.2015.5},
	journal-iso = {ACTA CYBERN-SZEGED},
	journal = {ACTA CYBERNETICA},
	volume = {22},
	unique-id = {2921814},
	issn = {0324-721X},
	abstract = {Big data and cloud computing are two phenomena, which have gained significant reputation over the last few years. In computer science the approach shifted towards distributed architectures and high performance computing. In case of geographical information systems (GIS) and remote sensing image analysis, the new paradigms have already been successfully applied to several problems, and systems have been developed to support processing of geographical and remote sensing data in the cloud. However, due to different circumstances many previous workflows have to be reconsidered and redesigned. Our goal is to show a way how the existing approaches to remote sensing image analysis can be advanced to take advantages of these new paradigms. The task aiming in shifting the algorithms shall require a moderate effort and must avoid the complete redesign and reimplementation of the existing approaches. We present the whole journey as a case study using an existing industrial workflow for demonstration. Nevertheless, we define the rules of thumb, which can come in hand when shifting any existing GIS workflows. Our case study is the workflow of waterlogging and flood detection, which is an operative task at the Institute of Geodesy, Cartography and Remote Sensing (FÖMI). This task in currently operational using a semi-automatic single machine approach involving multiple software. The workflow is neither efficient nor scalable, thus it is not applicable in emergency situations where quick response is required. We present an approach utilizing distributed computing, which enables the automated execution of this task on large input data with much better response time. The approach is based on the well-known MapReduce paradigm, its open-source implementation, the Apache Hadoop framework and the AEGIS geospatial toolkit. This enables the replacement of multiple software to a single, generic framework. Results show that significant performance benefits can be achieved at the expense of minor accuracy loss.},
	year = {2015},
	eissn = {2676-993X},
	pages = {57-79},
	orcid-numbers = {Giachetta, Roberto/0000-0002-3111-3396; Fekete, István/0000-0002-4089-4550}
}

@book{MTMT:3163236,
	title = {Távérzékelt felvételek elemzése},
	url = {https://m2.mtmt.hu/api/publication/3163236},
	isbn = {9789632844701},
	author = {Fekete, István and László, István},
	publisher = {ELTE Faculty of Informatics; Eötvös Loránd Tudományegyetem Informatikai Kar},
	unique-id = {3163236},
	year = {2014},
	orcid-numbers = {Fekete, István/0000-0002-4089-4550}
}

@{MTMT:2791192,
	title = {AMNIS - DESIGN AND IMPLEMENTATION OF AN ADAPTIVE WORKFLOW MANAGEMENT SYSTEM},
	url = {https://m2.mtmt.hu/api/publication/2791192},
	author = {Molnár, Bálint and Zsigmond, Máriás and Zoltán, Suhajda and Fekete, István},
	booktitle = {9th International Symposium on Applied Informatics and Related Areas - AIS2014},
	doi = {10.13140/2.1.2922.6565},
	unique-id = {2791192},
	abstract = {The experiences of introduction and operation of ERP systems have revealed that update of these software due to the
		constantly changing business processes demand huge resources. That is why the demand was formulated for a method
		that enables introducing new features in software system without any modification in program code according to the
		evolution of the organization. The objective of Amnis development project is to create a system with this adaptation
		capability using the basic idea of workflows that create documents during evaluation. In this article design and
		programming challenges are shown that had to be met during the development of Amnis, focusing on topics of effective
		data storage and queries, workflow control structures and workflow evaluation techniques.},
	year = {2014},
	orcid-numbers = {Molnár, Bálint/0000-0001-5015-8883; Fekete, István/0000-0002-4089-4550}
}

@article{MTMT:2061844,
	title = {Experimental study on graph-based image segmentation methods in the classification of satellite images},
	url = {https://m2.mtmt.hu/api/publication/2061844},
	author = {Dezső, Balázs and Giachetta, Roberto and László, István and Fekete, István},
	journal-iso = {EARSEL EPROC},
	journal = {EARSEL EPROCEEDINGS},
	volume = {11},
	unique-id = {2061844},
	issn = {1729-3782},
	year = {2012},
	eissn = {1729-3782},
	pages = {12-24},
	orcid-numbers = {Giachetta, Roberto/0000-0002-3111-3396; László, István/0000-0003-2971-486X; Fekete, István/0000-0002-4089-4550}
}

@article{MTMT:1945182,
	title = {Object-based image analysis in remote sensing applications using various segmentation techniques},
	url = {https://m2.mtmt.hu/api/publication/1945182},
	author = {Dezső, Balázs and Fekete, István and Dávid, Ákos Gera and Giachetta, Roberto and László, István},
	journal-iso = {ANN UNIV SCI BP R EÖTVÖS NOM SECT COMPUT},
	journal = {ANNALES UNIVERSITATIS SCIENTIARUM BUDAPESTINENSIS DE ROLANDO EOTVOS NOMINATAE SECTIO COMPUTATORICA},
	volume = {37},
	unique-id = {1945182},
	issn = {0138-9491},
	abstract = {At Eötvös Loránd University (ELTE), Faculty of Informatics extensive education, research and development activity is carried out in geoinformatics, in cooperation with Institute of Geodesy, Cartography and Remote Sensing (FÖMI). It includes the teaching of subject "Remote Sensing Image Analysis", research of segment-based classification of remote sensing images and its applications in operational projects.
		Investigation of segmentation methods is embedded into the classification problem. Segments are homogeneous areas of images, consisting of neighboring pixels. Segment membership of pixels conveys valuable geometric information to classification step. This article gives a summary on several merge-based and cut-based segmentation methods.
		The application of segmentation is not only an option, but a necessity in the processing of very high resolution images, as their pixels usually cannot be interpreted individually. Segments are assigned with several attributes (e.g. texture) derived from geometrical properties. This leads to
		the advanced approach called Object-based Image Analysis (OBIA).
		As an application, the task of delimiting tree groups and scattered trees in pastures will be presented in detail. Three further applications will also be shortly introduced.},
	year = {2012},
	pages = {103-120},
	orcid-numbers = {Fekete, István/0000-0002-4089-4550; Giachetta, Roberto/0000-0002-3111-3396; László, István/0000-0003-2971-486X}
}

@inproceedings{MTMT:2113530,
	title = {Object-based image analysis of pasture with trees and red mud spill},
	url = {https://m2.mtmt.hu/api/publication/2113530},
	author = {László, István and Ócsai, Katalin and Gera, Dávid and Giachetta, Roberto and Fekete, István},
	booktitle = {Remote Sensing and Geoinformation not only for Scientific Cooperation},
	unique-id = {2113530},
	abstract = {Abstract. This article shows the possibilities of object-based analysis of very high resolution satel-lite and aerial images in three applications from the areas of agriculture and disaster monitoring: the detection of scattered trees and bushes on pasture (eligibility issues in Land Parcel Identifica-tion System), the delineation of industrial red sludge spill and ragweed monitoring (mapping of ragweed spots in agricultural areas). To achieve proper results, we need to create image objects fit-ting land cover objects and classify them to predefined classes. The key step of object-based ap-proach is segmentation, that is, the division of image to contiguous sets of spectrally similar pixels. Beside implementing and examining different segmentation algorithms, the authors have used the Definiens / eCognition software in operational applications. The results achieved justify that the accuracy of object-based classification is comparable to pixel-based one, and the analysis of tex-tural and shape properties can further increase accuracy and appropriateness of procedures.
		Keywords. Segmentation, object-based image analysis, Land Parcel Identification System, toxic spill, ragweed monitoring},
	year = {2011},
	pages = {423-431},
	orcid-numbers = {László, István/0000-0003-2971-486X; Giachetta, Roberto/0000-0002-3111-3396; Fekete, István/0000-0002-4089-4550}
}